This invention relates to vector quantization at a low bit rate of a time sequential signal which is typically an audio signal or a video signal. More particularly, this invention relates to a vector quantization method and to a vector quantization device.
In such vector quantization, the time sequential signal is divided into consecutive frames. The bit rate is lowered on an average either by reducing the number of bits assigned to each frame or by using a long frame length. This invention is based on use of a long frame length.
In a conventional vector quantizing device, use of a long frame length has resulted in a deteriorated reproducibility of time sequential characteristics. The reproducibility of the time sequential characteristics is therefore raised primarily by subdivision of each frame into subframes and by calculation of feature or characteristic parameters of each subframe.
An article is contributed by Noboru Sugamura and another in the Japanese language to Densi Tusin Gakkai Ronbunsi (the Transactions of the Electronics, Information, and Telecommunication Engineers of Japan), Volume J64-A, No. 8 (August, 1981), pages 599 to 606, under the title in translation of "Speech Data Compression by LSP Speech Analysis-Synthesis Technique". According to this Sugamura et al article, quantized subframe feature parameters are decided in connection with the subframes by linear interpolation between a quantized frame feature parameter for a current frame of the time sequential signal and another quantized frame parameter decided for a previous frame.
The reproducibility of the time sequential characteristics is raised alternatively by decision of subframe feature parameters and collective quantization of the subframe feature parameters by a matrix quantizer. In this matrix quantization, a quantized subframe feature parameter is produced for a desired subframe directly without interpolation.
An example is disclosed by D. Y. Wong, B. H. Juang, and D. Y. Cheng in a paper submitted to the IEEE ICASSP 83 and recorded in the IEEE Proceedings ICASSP, 1983, pages 65 to 68, under the title of "Very Low Data Rate Speech Compression with LPC Vector and Matrix Quantization". Another example is described in an article contributed by Chieh Tsao and Robert M. Gray to the IEEE Transactions on Acoustics, Speech, and Signal Processing, Volume ASSP-33, No. 3 (June 1985), pages 537 to 545, under the title of "Matrix Quantizer Design for LPC Speech Using the Generalized Lloyd Algorithm". In both of these examples, a vector quantization codebook is referred to on quantizing each subframe feature parameter.
In vector quantization, use of the linear interpolation results in a much deteriorated reproducibility of the time sequential characteristics when a frame includes a transition of the time sequential signal. Furthermore, the linear interpolation is not necessarily an optimum interpolation function for the feature parameters which should be subjected to interpolation.
For matrix quantization, it is possible to design various interpolation functions. Such an interpolation function, however, represents an average characteristic for each frame as a whole and is incapable of reproducing time sequential variations of the time sequential signal except for the time sequential characteristics for which the interpolation function is designed.
It is known on the other hand in theory that vector quantization has an asymptotic characteristic which is proportional to the number of bits per vector dimension. This is described in an article contributed by Tom D. Lookabaugh and Robert M. Gray to the IEEE Transactions on Information Theory, Volume 35, No. 5 (September 1989), pages 1020 to 1033, under the title of "High-Resolution Quantization Theory and the Vector Quantizer Advantage".
It follows therefore when the matrix quantization is resorted to that the time sequential characteristics are more degraded than those achieved by the linear interpolation when a small number of bits are used per vector dimension with each frame subdivided into a great number of subframes. When this great number of subframes is applied to the vector quantization with the number of vector dimensions increased, design of the interpolation function gives rise to similar problems as in the matrix quantization.
In the meantime, a prior United States patent application was filed Feb. 9, 1994, under Ser. No. 193,596 by Kazunori Ozawa, assignor to the present assignee. In accordance with this copending Ozawa patent application, each frame of a voice or speech signal has a long frame length which is typically 40 milliseconds long. Each frame is subdivided into a plurality of subframes, such as first through fifth subframes. Line spectrum pairs (LSP) are extracted as subframe feature parameters from only at least one subframe, such as the fifth subframe, of each frame. For others of the subframes, such feature parameters are interpolated with reference to an interpolation codebook, which is trained. The subframe feature parameters are quantized by using at least two vector quantization codebooks. It should be noted that the present invention of the instant inventor is similar in respects of use of a long frame length, a plurality of subframes, extraction of subframe feature parameter vectors from at least two subframes of each frame, vector quantization codebooks, and an interpolation codebook.